AIMC Topic: Lung Neoplasms
Clear Filters Showing 511 to 520 of 1668 articles
Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Apr 4, 2024
BACKGROUND: Pneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) rad...
Machine learning-driven prediction of brain metastasis in lung adenocarcinoma using miRNA profile and target gene pathway analysis of an mRNA dataset.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Apr 3, 2024
BACKGROUND: Brain metastasis (BM) is common in lung adenocarcinoma (LUAD) and has a poor prognosis, necessitating predictive biomarkers. MicroRNAs (MiRNAs) promote cancer cell growth, infiltration, and metastasis. However, the relationship between th...
Boosting predictive models and augmenting patient data with relevant genomic and pathway information.
Computers in biology and medicine
Apr 3, 2024
The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models,...
Identification and validation of an immune-derived multiple programmed cell death index for predicting clinical outcomes, molecular subtyping, and drug sensitivity in lung adenocarcinoma.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Apr 2, 2024
OBJECTIVES: Comprehensive cross-interaction of multiple programmed cell death (PCD) patterns in the patients with lung adenocarcinoma (LUAD) have not yet been thoroughly investigated.
Real-World Outcomes of Patients with Advanced Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Cancer in Canada Using Data Extracted by Large Language Model-Based Artificial Intelligence.
Current oncology (Toronto, Ont.)
Apr 2, 2024
Real-world evidence for patients with advanced -mutated non-small cell lung cancer (NSCLC) in Canada is limited. This study's objective was to use previously validated DARWEN artificial intelligence (AI) to extract data from electronic heath records ...
Deceptive learning in histopathology.
Histopathology
Mar 31, 2024
AIMS: Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the...
Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation.
European radiology
Mar 27, 2024
OBJECTIVE: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.
A deep learning model for translating CT to ventilation imaging: analysis of accuracy and impact on functional avoidance radiotherapy planning.
Japanese journal of radiology
Mar 27, 2024
PURPOSE: Radiotherapy planning incorporating functional lung images has the potential to reduce pulmonary toxicity. Free-breathing 4DCT-derived ventilation image (CTVI) may help quantify lung function. This study introduces a novel deep-learning mode...
Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.
Medical physics
Mar 26, 2024
BACKGROUND: The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to...
Robust deep learning from incomplete annotation for accurate lung nodule detection.
Computers in biology and medicine
Mar 26, 2024
Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32065
- Neural Networks, Computer 30249
- Algorithms 27433
- Deep Learning 26935
- Artificial Intelligence 24866
- Robotics 13394
- Image Processing, Computer-Assisted 9746
- Retrospective Studies 9358
- Magnetic Resonance Imaging 6353
- Reproducibility of Results 5671
- Tomography, X-Ray Computed 4869
- Support Vector Machine 4774
- Computational Biology 4337
- Brain 4132
- Computer Simulation 3936
Recent Journals
- Scientific reports 6855
- Sensors (Basel, Switzerland) 4794
- PloS one 4219
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1920
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1178
- Journal of chemical information and modeling 1070
- Nature communications 1054
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 877
- Journal of medical Internet research 867
- IEEE transactions on neural networks and learning systems 854